1. Technical Field
The present disclosure relates generally to a matchmaker or recommender service for matching a first set of entities with a second set of entities.
2. Description of the Related Art
With myriad goods and services available, consumers frequently wish to narrow down the scope of options when choosing from a variety of possible products or service providers. In an online or e-commerce environment, simple searches and filtering based strictly on information about the products or service providers do not take into account an individual consumer's preferences, and thus typically provide only impersonal search results that may be tailored to reflect availability of the product or service based on the consumer's geographic location. Recommendations based on known consumer preferences—whether the consumer's own preferences or the preferences of other consumers similarly situated to the searching consumer—can be used to customize search results to those that are thought to be of most interest to the consumer. Conversely, an advertiser of a good or service wishing to maximize the effectiveness of an advertising campaign may wish to target a particular set of consumers with direct advertising.
Two main approaches to recommendation or “matchmaking” are collaborative filtering and content-based filtering. Collaborative filtering selects or orders search results based on computed values derived from known preferences for many consumers, whereas content-based filtering leverages knowledge about the products and services, and optionally about the individual consumer seeking recommendations. Collaborative and content-based filtering may be used in tandem.